Machine learningPrivacy-preserving analysis
安全多方计算
安全多方计算（SMPC）是一种密码学范式，它使两个或多个参与方能够联合计算其私有输入上的函数，而无需相互揭示这些输入。SMPC 由 Andrew Yao 于 1982 年通过其开创性的混淆电路（garbled circuit）构造提出，它提供了基于计算困难性假设的可证明隐私保证。它支撑着现代隐私保护数据分析，使得在金融、医疗保健和机器学习等领域的敏感数据集上能够进行协作计算。
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来源
- Yao, A. C. (1982). Protocols for secure computations. 23rd Annual Symposium on Foundations of Computer Science, 160–164. DOI: 10.1109/SFCS.1982.38 ↗
如何引用本页
ScholarGate. (2026, June 2). Secure Multi-Party Computation (SMPC). ScholarGate. https://scholargate.app/zh/privacy/secure-multiparty-computation
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